Methods and apparatus to detect spillover

ABSTRACT

Methods and apparatus to improve the accuracy of crediting media exposure through detecting reverberation indicative of spillover. Example disclosed methods involve determining periods of loudness in media presented by a media presentation device, and identifying a quantity of the periods of loudness that satisfy a duration threshold. Disclosed example methods also involve calculating a ratio by dividing the quantity of the periods of loudness that satisfy the duration threshold by a total number of periods of loudness in the media. Disclosed example methods also involve marking the media as usable to credit a media exposure if the ratio satisfies a loud threshold.

RELATED APPLICATIONS

The patent claims benefit of U.S. Provisional Patent Application Ser.No. 62/192,889, filed Jul. 15, 2015, which is hereby incorporated byreference in its entirety.

FIELD OF THE DISCLOSURE

This disclosure relates generally to media monitoring, and, moreparticularly, to methods and apparatus to detect spillover.

BACKGROUND

Audience measurement of media, such as television, music, movies, radio,Internet websites, streaming media, etc., is sometimes carried out bymonitoring media exposure of panelists who are statistically selected torepresent particular demographic groups. Using various statisticalmethods, the captured media exposure data is processed to determine thesize and demographic composition of the audience(s) for programs ofinterest. The audience size and demographic information is valuable toadvertisers, broadcasters and/or other entities. For example, audiencesize and demographic information is a factor in the placement ofadvertisements, as well as a factor in valuing commercial time slotsduring a particular program.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example system including meters with spillovermanagers to detect spillover to reduce media monitoring inaccuracies.

FIG. 2 illustrates an example implementation of an example meter of FIG.1.

FIGS. 3A, 3B, and 3C illustrate an example portion of an audio signalanalyzed by the example spillover manager of FIGS. 1 and 2.

FIGS. 4A, 4B, and 4C illustrate another example portion of an audiosignal analyzed by the example spillover manager of FIGS. 1 and 2.

FIG. 5 is a flow diagram representative of example machine readableinstructions that may be executed to implement the example meter ofFIGS. 1 and 2 to award media with media exposure credit.

FIG. 6 is a flow diagram representative of example machine readableinstructions that may be executed to implement the example spillovermanager of FIGS. 1 and 2 to detect spillover.

FIGS. 7A and 7B are flow diagrams representative of example machinereadable instructions that may be executed to implement the examplereverberation analyzer of FIG. 2 to detect periods of loudness in anaudio signal.

FIG. 8 is a block diagram of an example processor system structured toexecute the example machine readable instructions represented by FIGS.5, 6, and/or 7A, 7B, to implement the example spillover manager of FIGS.1 and 2 and/or the example meters of FIGS. 1 and 2.

DETAILED DESCRIPTION

Examples disclosed herein may be used to improve the accuracy ofcrediting media exposure through detecting reverberation indicative ofspillover. An audience measurement entity (AME) enlists persons toparticipate in measurement panels. Such persons (e.g., panelists) agreeto allow the AME to measure their exposure to media (e.g., televisionprogramming, radio programming, Internet, advertising, signage, outdooradvertising, etc.). To associate media exposure data (i.e., dataindicative of media presentation) with panelist demographics, the AMEmonitors media device(s) and/or panelist(s) using media monitoringmeters. In some examples, meters (e.g., stationary meters) are placedwith and/or near media presentation devices (e.g., televisions, stereos,speakers, computers, etc.) within a home or household. For example, ameter may be placed in a room with a television and another meter may beplaced in a different room with another television. In some examples,personal portable metering devices (PPMs), which are also known asportable metering devices or portable personal (or people) meters, areused to monitor media exposure of panelists to media. A PPM is anelectronic device that is typically worn (e.g., clipped to a belt orother apparel) or carried by a panelist. The term “meter” as used hereinrefers generally to stationary meters and/or portable meters.

A panelist home may present challenges to the meters that monitorpresentation devices. For example, a panelist home often includesmultiple media presentation devices, each configured to present media tospecific viewing and/or listening areas (e.g., a family room, a bedroom,a kitchen, etc.) located within the home. Meters that are located in oneof the viewing and/or listening areas are configured to detect any mediabeing presented in the viewing and/or listening area and to credit themedia as having been presented. Thus, meters operate on the premise thatany media detected by the meter is media that was presented in thatparticular viewing and/or listening area. However, in some cases, ameter may detect media that is emitted by a media presentation devicethat is not located within the viewing or listening proximity of apanelist in the room with the meter thereby causing the detected mediato be improperly credited to the panelist currently associated with themonitored area (via, for example, a people meter).

The ability of the meter to detect media being presented outside of theviewing and/or listening proximity of the panelist is referred to as“spillover” because the media being presented outside of the viewingand/or listening proximity of the panelist is “spilling over” into thearea occupied by the media identifying meter and may not actually fallwithin the attention of the panelist. Spillover may occur, for example,when a television in a particular room is powered off, but a meterassociated with that television detects media being presented on a mediapresentation device in a different room of the panelist home or of anadjacent home (e.g., a neighbor's condominium or apartment). In such anexample, the meter improperly credits the media as being presented onthe media presentation device it monitors, even though no suchpresentation occurred.

Another effect, referred to as “hijacking,” occurs when a meter detectsdifferent media being presented at multiple media presentation devicesat the same time. For example, a meter in a kitchen may detect aparticular media program being presented on a media presentation devicein the kitchen, but the meter may also detect a different media programthat is being presented on a different media presentation device in aliving room. In such an example, the media presented by the mediapresentation device in the living room may, in some cases, have signalsthat overpower the signals associated with the media being presented bythe media presentation device in the kitchen. As a result, the mediaidentifying meter in the kitchen may be “hijacked” by the signals fromthe living room and the meter may inaccurately credit the media beingpresented in the living room and fail to credit the media beingpresented in the kitchen.

Example disclosed herein may be used to detect occurrences of spilloverbased on loudness and quietness characteristics of audio signal to moreaccurately credit media with exposure credits. An audio signal detectedclose to a media presentation device is characterized by short periodsof relative loudness separated by short periods of relative quietness(e.g., periods of quiet between syllables in speech, etc.). As the audiosignal from a media presentation device travels, reverberation isintroduced into the audio signal as the audio signal propagates throughthe home of the panelist and reflects off some surfaces (e.g., walls,doors, etc.) and/or is absorbed by some surfaces (e.g., paddedfurniture, etc.). Characteristics of a room, such as open/closed doors,movement and/or placement of furniture, acoustic characteristics of roomlayouts, wall construction, floor coverings, ceiling heights, etc.,affect quality of the audio signal. The reverberation reduces thedetectability of the short periods of quietness because the reflectionsdelay some audio components and add noise that may overlap with theperiods of quietness. Thus, as an audio signal propagates through anenvironment and short periods of quietness are lost, and periods ofloudness become longer.

In examples disclosed herein, a meter captures an audio signal of themedia presentation through an audio capture device (e.g., a microphone).An example spillover manager of the meter detects periods of relativeloudness and periods of relative quietness in the audio signal. Todetect these periods, the spillover manager samples the audio signal ata sampling frequency (e.g., 2,000 samples per second, 8,000 samples persecond, 40,000 samples per second, etc.). The example spillover managerdetermines a sample magnitude for each sample, where the samplemagnitude is the absolute value of the amplitude of the audio signal atthe sample.

Using the sample magnitude, the example spillover manager determineswhether the corresponding sample is a loud sample or a quiet samplerelative to previous sample values. If the previous sample (n−1) was aquiet sample, the example spillover manager determines that the currentsample (n) is a loud sample if the difference between the value of thecurrent sample (n) and the value of a pervious sample (n−1) satisfies(e.g., is greater than) a loud threshold. Otherwise, the examplespillover manager determines that the current sample (n) is a quietsample. If the previous sample (n−1) was a loud sample, the examplespillover manager determines that the current sample (n) is a quietsample if the sample value of the current sample (n) satisfies (e.g., isless than) a quiet threshold. Otherwise, the example spillover managerdetermines that the current sample (n) is a loud sample. The quietthreshold is set at a value below the sample value when the samplestransitioned from a quiet sample to a loud sample. In this manner, whena next sample (n+1) is compared to the quiet threshold, the examplespillover manager can detect relative periods of quietness even when theaudio sample overall has a high amplitude (e.g., when the audio volumeis loud). Alternatively, in some examples, the quiet threshold is set ata value below the highest sample value since the last transition from aquiet sample to a loud sample (e.g., the last peak value).

A period of loudness begins when the audio signal transitions from quietto loud (e.g., the previous sample (n−1) is relatively quiet and thecurrent sample (n) is relatively loud). In some examples, the period ofloudness ends when the audio signal transitions from loud to quiet(e.g., the previous sample (n−1) is relatively loud and the currentsample (n) is relatively quiet). Alternatively or additionally, in someexamples, the period of loudness does not end until a threshold numberof relatively quiet samples occur after the audio signal transitionsfrom loud to quiet. For example, if after the audio signal transitionsfrom loud to quiet, there are two relatively quiet samples followed by arelatively loud sample, the period of loudness may be considered not tohave ended.

The period of loudness has a sample duration that is measured in thenumber of audio samples between the two transitions. For example, aperiod of loudness may have a sample duration of 1,837 samples. A timeduration, in seconds, for a period of loudness depends on the samplingfrequency of the audio signal. For example, if an audio signal issampled at 8,000 samples per second, the period of loudness with a 1,837sample duration has a 0.23 second duration. In some examples, the AMEdefines sample duration ranges (sometimes referred to as “sampleduration buckets”). For example, duration ranges may be defined in 200sample increments, (e.g., a 1-200 sample duration range, a 201-400sample duration range, a 401-600 sample duration range, etc.). In suchexamples, the periods of loudness are assigned to a sample durationrange based on the sample duration of the period of loudness. Forexample, a period of loudness with a 347 sample duration is assigned toa 201-400 sample duration range. In some such examples, a quantity ofperiods of loudness is tracked for each duration range. In some example,the samples of the audio signal and sample magnitudes corresponding tothe period of loudness are discarded after assigning the period ofloudness to a sample duration range.

The example spillover manager determines if spillover occurred for aninterval of the audio signal (e.g., a one-second interval, a five-secondinterval, a ten-second interval, etc.). For example, the spillovermanager may determine if spillover occurred in five-second intervals ofthe audio signal. For a particular interval, the example spillovermanager identifies the periods of loudness in the interval, determineswhich of the periods of loudness have a short duration, and calculates ashort loudness ratio (R_(SL)) based on the number of detected periods ofloudness with a short time or sample duration and the total number ofdetected periods of loudness in accordance with Equation 1 below.

$\begin{matrix}{R_{SL} = \frac{{POL}_{S}}{{POL}_{T}}} & {{Equation}\mspace{14mu} 1}\end{matrix}$

In Equation 1 above, POL_(S) is the quantity of periods of loudness witha short time or sample duration, and POL_(T) is the total quantity ofperiods of loudness. The example spillover manager determines that aperiod of loudness has a short time or sample duration if the period ofloudness has a time or sample duration below a time or sample durationthreshold. In some examples, the time or sample duration threshold isselected so that in blocks of the audio signal where spillover did notoccur, the short loudness ratio is greater than a loudness ratiothreshold (e.g., 50%, 66%, etc.). For example, the sample durationthreshold may be 1,800 samples. In such an example, the spillovermanager designates periods of loudness with sample durations below 1,800samples as having a short sample duration. For example, a five-secondblock of an audio sample may have 140 total periods of loudness and 76periods of loudness with short sample durations. In such an example, theshort loudness ratio is

$54\% \mspace{14mu} {\left( {\frac{76}{140} \times 100\%} \right).}$

In such an example, if the loudness ratio threshold is 50%, thespillover manager determines that spillover did not occur for that fivesecond interval of the audio signal.

FIG. 1 depicts an example system 100 including example meters 102, 104,106 that include corresponding spillover manager 107 to detect spilloverand reduce media monitoring inaccuracies associated with incorrectlycrediting media with exposure credit based on detecting spillover audioassociated with that media. In the illustrated example, the meters 102,104 are stationary meters that are placed in, on, and/or near mediapresentation devices 108, 110 (e.g., televisions, stereos, speakers,computers, game consoles, etc.) to monitor media (e.g., televisionprogramming, radio programming, movies, songs, advertisements,Internet-based programming such as websites and/or streaming media,etc.) presented by the media presentation devices 108, 110. In theillustrated example, a panelist 112 wears a personal portable meteringdevice 106 (PPM), to monitor media presented by the media presentationdevices 108, 110 near the panelist 112.

The example meters 102, 104, 106 process the detected media to extractcodes and/or metadata, and/or to generate signatures for use inidentifying the media and/or a station (e.g., a broadcaster) thatprovides the media. Identification codes, such as watermarks, ancillarycodes, etc. may be embedded in or otherwise transmitted with media.Identification codes are data inserted into media to uniquely identifybroadcasters and/or the media, and/or are provided with the media forother purposes such as tuning (e.g., packet identifier headers (“PIDs”)used for digital broadcasting).

Codes are typically extracted using a decoding operation. Signatures area representation of one or more characteristic(s) of the media signal(e.g., a characteristic of the frequency spectrum of the signal). Codes,metadata, signatures, etc. collected and/or generated by the meters 102,104, 106 for use in identifying the media and/or a station thattransmits the media are part of media exposure data collected by themeters 102, 104, 106.

In the illustrated example, the meters 102, 104, 106 are communicativelycoupled with a home processing system 114 via a wireless and/or ahardwired connection. In illustrated example, the home processing system114, from time to time, collects media exposure data from the meter(s)in a panelist home and communicates the collected media exposure data toan audience measurement entity (AME) 118 via a network 119 (e.g., theInternet, a local area network, a wide area network, a cellular network,etc.) via wired and/or wireless connections (e.g., a cable/DSL/satellitemodem, a cell tower, etc.). Additionally or alternatively, in someexamples, the meters 102, 104, 106 may communicate the collected mediaexposure data to the AME 118 via the network 119 (e.g., via a cellularnetwork, etc.).

In the illustrated example, the AME 118 includes an example monitoringdatabase 120 and an example server 122. The example server 122 collectsthe media exposure data from the meters 102, 104, 106 and stores thecollected media exposure data in the example monitoring database 120.The example server 122 processes the collected media exposure data bycomparing the codes, metadata, and/or signatures in the collected mediaexposure data to reference codes and/or signatures in a referencedatabase to identify the media and/or station(s) that transmit themedia. Examples to process the codes and/or signatures in the collectedmedia exposure data are described in U.S. patent application Ser. No.14/473,670, filed on Aug. 29, 2014, which is hereby incorporated hereinby reference in its entirety. The example server 122 awards mediaexposure credits to media identified in the collected media exposuredata. In some examples, the media exposure credits are associated withdemographic information in the panelist database corresponding to apanelist 112 associated with the meters 102, 104, 106 that collected themedia exposure data.

The example AME 118 maintains a panelist database to store panelistnames, demographic information, and/or other information collected frompanelists 112 during an enrollment process. During the enrollmentprocess, the AME 118 of the illustrated example contracts and/or enlistspanelists 112 to be part of the panelist database. Panelist 112 may beenrolled into the panelist database using any suitable technique (e.g.,random selection, statistical selection, phone solicitations, Internetadvertisements, surveys, advertisements in shopping malls, productpackaging, etc.). Demographic information (e.g., gender, occupation,salary, race and/or ethnicity, marital status, highest completededucation, current employment status, etc.) is obtained from thepanelist 112 when the panelist 112 joins (e.g. enrolls in) a panel.Additionally, the demographic information may be obtained throughvarious methods during the enrollment process (e.g., via a telephoneinterview, by having the panelist complete an online or paper survey,etc.).

In the example system 100 of FIG. 1, an example audio signal 124 of themedia propagates from the media presentation device 108. The illustratedexample of FIG. 1 shows two example paths that the audio signal 124 maytake. The audio signal 124 of the illustrated example is detected by theexample meter 102, which is relatively close to the media presentationdevice 108, and is detected by the example meters 104, 106 which arerelatively far away (e.g., in another room) from the media presentationdevice 108 compared to the proximity of the meter 102 to the mediapresentation device 108. When the audio signal 124 is detected by themeter 102, the audio signal 124 is characterized by periods of relativeloudness separated by short periods of quiet (e.g., periods of quietbetween syllables in speech, etc.) because the meter 102 is close to thesource (e.g., the media presentation device 108) of the media. As theaudio signal 124 propagates farther away from its source, it isdistorted by being reflected and/or defused off of hard surfaces (e.g.,walls, ceilings, flooring, etc.), and/or being partially absorbed bysoft surfaces (e.g., furniture, carpet, etc.). As the audio signal 124is distorted, the relatively loud portions of the audio signal 124overlap into the periods of quietness. As a result, fewer short periodsof loudness are detectable in the distantly propagated audio signal 124,and periods of loudness that are observed in the distantly propagatedaudio signal tend to be the longer periods of loudness that have alonger time duration in the audio signal 124 when it was initiallyemitted by the media presentation device 108. This change in the periodsof loudness characteristics is referred to herein as reverberation.Thus, the audio signal 124 detected at meters 104, 106 farther from(e.g., in a different room) the media presentation device 108 will bedifferent than the audio signal 124 detected at the adjacent meter 102due to reverberation characteristics in the distantly propagating audiosignal 124.

For example, if the audio signal 124 is captured (e.g., via amicrophone, etc.) by the example meter 102 near the media presentationdevice 108, the spillover manger 107 does not detect the reverberationcharacteristics and determines that spillover did not occur. As anotherexample, if the audio signal 124 is captured by a distantly locatedmeter 104, 106 that is located relatively far (e.g., in another room)from the media presentation device 108, the spillover manager 107detects the reverberation characteristics and determines that spilloverdid occur. Examples to detect the reverberation characteristics aredescribed below in connection with FIGS. 2, 3, and 4.

FIG. 2 illustrates an example implementation of an example meter 200that include a spillover manager 107 to detect reverberationcharacteristics in an audio signal 124 indicative of spillover. Theexample meter 200 may be used to implement one or more of the examplemeters 102, 104, 106 of FIG. 1. For example, the example meter 200 maybe a stationary meter (e.g., the meters 102, 104 of FIG. 1) or may be aportable meter (e.g., the meter 106 of FIG. 1). The example meter 200includes an example receiver 202 (e.g., a microphone, etc.) to receivean audio signal 124 from media presentation devices (e.g., mediapresentation devices 108, 110 of FIG. 1). In the illustrated example,the meter 200 includes an example collector 204 to extract codes and/orsignatures from the audio signal 124 received by the receiver 202. Theextracted codes and/or signatures are used to identify broadcasters,channels, stations, and/or the media corresponding to the audio signal124. The example collector 204 samples the audio signal 124 at asampling frequency (e.g., 2,000 samples per second, 8,000 samples persecond, 40,000 samples per second, etc.) to digitize the audio signal124 to extract codes from the audio signal 124 and/or generatesignatures based on the audio signal 124 in the digital domain. Examplesof extracting codes and/or generating signatures are disclosed in U.S.Pat. No. 5,481,294, which is hereby incorporated herein by reference inits entirety. The example collector 204 extracts codes and/or generatessignatures to generate and collect media exposure data for an interval(e.g., a one-second interval, a five-second interval, etc.) of the audiosignal 124. For example, the collector 204 may extract a code and/orgenerate a signature for one-second periods to determine which media apanelist (e.g., the panelist 112 of FIG. 1) was exposed to over thoseone-second periods of time. In some examples, the collector 204 adds atimestamp to the exposure data with a time and/or date corresponding towhen the audio signal 124 corresponding to the potential exposure wasreceived.

The example meter 200 includes an example media evaluator 206 and anexample media exposure database 207. The example media evaluator 206marks (e.g., set a flag, etc.) media exposure data collected by thecollector 204 to indicate that the media exposure data is usable toaward exposure credit to the media identified by the media exposuredata. In the illustrated example, the media evaluator 206 marks (e.g.,sets a flag, etc.) the exposure data as usable for awarding exposurecredit based on instructions from the spillover manager 107. In someexamples, if the media evaluator 206 does not receive instructions tomark the media exposure data from the spillover manager 107 as usablefor awarding exposure credit, the media evaluator 206 discards the mediaexposure data. In some examples, the media evaluator 206 addsidentifying information (e.g., a meter identifier, a panelistidentifier, etc.) to the media exposure data marked as usable forawarding exposure credit. The example media exposure database 207 storesthe media exposure data. In some examples, the media exposure database207 stores media exposure data marked by the mediate evaluator 206 asusable for awarding exposure credit. Alternatively, in some examples,the media exposure database 207 stores media exposure data regardless ofwhether the media exposure data is marked by the mediate evaluator 206as usable for awarding exposure credit.

The example meter 200 includes an example transmitter 208 to transmitthe media exposure data to the AME 118. In the illustrated example, fromtime to time (e.g., hourly, daily, weekly, etc.), the transmitter 208sends media exposure data stored in the media exposure database 207 tothe AME 118. Alternatively or additionally, in some examples, thetransmitter 208 sends media exposure data as it is marked by the mediaevaluator 206 (e.g., if there the meter 200 is connected to a network).The example transmitter 208 transmits the media exposure data via wirednetworks (e.g., Ethernet, phone line, etc.) and/or wireless networks(e.g., Wide Area networks, cellular networks, etc.). In some examples,the transmitter 208 transmits the media exposure data to a base station(e.g., a stationary meter 102, 104, a home computer, a home processingsystem 114, etc.) via a wireless connection (e.g., Bluetooth, Near FieldCommunication, Wi-Fi, etc.) or via a wired connection (e.g., UniversalSerial Bus (USB), etc.) so that the base station can send the mediaexposure data to the AME 118. In some examples, the transmitter 208transmits all of the media exposure data regardless of whether it ismarked as usable to award exposure credit so that the AME 118 canfurther analyze all of the media exposure data collected by the meter200. In other examples, the transmitter 208 transmits only the mediaexposure data that the media evaluator 206 marked as being usable toaward exposure data.

In the illustrated example of FIG. 2, the spillover manager 107 detectsspillover based on the audio signal 124 and instructs the mediaevaluator 206 to mark the corresponding media exposure data as usable toaward media exposure credit when spillover does not occur. The examplespillover manager 107 includes an example audio sampler 210, an examplereverberation analyzer 212, and an example spillover detector 214. Theaudio sample 210 of the illustrated example samples the audio signal 124at a sampling frequency (e.g., 2,000 samples per second, 8,000 samplesper second, 40,000 samples per second, etc.) that is sufficiently fastto detect reverberation characteristics. Alternatively, in someexamples, the audio sampler 210 obtains the samples of the audio signal124 generated by the collector 204. In some such examples, the audiosampler 210 obtains one sample out of every Nth samples (e.g., everyother sample, one sample out of every ten samples, one sample out ofevery one hundred samples, etc.) produced by the collector 204. Forexample, if the audio sampler 210 receives samples of the audio signal124 from the collector 204 that has a sampling frequency of 40,000samples per second, the audio sampler 210 may obtain every 10th sample(e.g., 4,000 samples per second) and discard or ignore the remainingsamples. The example audio sampler 210 determines the absolute value ofthe magnitude of each sample and organizes the samples into an audioblock representing a time duration of the audio sample 124 (e.g., onesecond, five seconds, ten seconds, etc.) corresponding to the timeduration of media exposure data generated by the collector 204. Forexample, audio samples provided by the audio sampler 210 correspond to asampling frequency of 8,000 samples per second. In such examples, theaudio sampler 210 may use every 10th sample and organize an audio blockthat includes five seconds worth of samples. In such examples, the audioblock includes 4,000 samples.

In the illustrated example of FIG. 2, the reverberation analyzer 212analyzes a portion of the audio signal 124 for spillover by determiningwhether reverberation characteristics are present in the portion of theaudio signal 124. For example, the reverberation analyzer 212 obtainsnumerous audio blocks from the audio sampler 210 corresponding todifferent portions of the audio signal. The example reverberationanalyzer 212 analyzes an audio block corresponding to a portion of theaudio signal 124 to detect periods of loudness within the audio block.In the illustrated example, the reverberation analyzer 212 determines aquantity of the periods of loudness within the audio block have sampledurations that satisfy (e.g., are less than) a duration threshold. Theexample reverberation analyzer 212 calculates a ratio for the audioblock by dividing the quantity of the periods of loudness that satisfythe duration threshold within the audio block by the total number ofperiods of loudness detected in the audio block as shown in Equation 1above.

In the illustrated example, the example reverberation analyzer 212determines that a period of loudness starts when a previous sample (n−1)is determined to be relatively quiet and the current sample (n) isdetermined to be relatively loud. In some examples, the examplereverberation analyzer 212 determines that the period of loudness endswhen a previous sample (n−1) is determined to be relatively loud and thecurrent sample (n) is determined to be relatively quiet. Alternativelyor additionally, in some examples, the period of loudness does not enduntil a threshold number of relatively quiet samples occur after theaudio signal transitions from loud to quiet.

The sample duration of a period of loudness is the number of samplesbetween the beginning of the period of loudness and the end of theperiod of loudness. For example, if the reverberation analyzer 212determines that the 257th sample in an audio block is relatively quietand the 258th sample of the audio block is relatively loud, thereverberation analyzer 212 would determine that a period of loudnessbegins at the 258th sample. If, for example, the reverberation analyzer212 determines that the 663rd sample in the same audio block isrelatively loud and the 664th sample of the audio block is relativelyquiet, the reverberation analyzer 212 determines that the period ofloudness ends at the 663rd sample. In such an example, the reverberationanalyzer 212 determines that the period of loudness begins at the 258thsample and ends at the 663th sample has a sample duration of 406 samples(664th sample-258th sample). In some examples, the reverberationanalyzer 212 determines that the period of quiet ends after it detects athreshold number (e.g., three, five, ten, etc.) of quiet samples afterthe audio samples in the audio block transition from a relatively loudsample to a relatively quiet sample. For example, if the reverberationanalyzer 212 determines that the 667th sample of the audio block isrelatively loud, the reverberation analyzer 212 may determine that theperiod of loudness did not end because the number of relatively quietsamples do not satisfy (e.g., are not greater than) a threshold numberof quiet samples.

The example reverberation analyzer 212 determines that a sample is loudif the previous sample (n−1) is relatively quiet and the magnitude ofthe current sample (n) satisfies (e.g., is greater than) a loudthreshold. The example reverberation analyzer 212 determines the loudthreshold based on the amplitude of the quiet sample when the audiosignal 124 last transitioned from a relatively loud sample to arelatively quiet sample. Alternatively, in some examples, the examplereverberation analyzer 212 determines the loud threshold based on thesample with the lowest magnitude since the current period of quietnessbegan. In some examples, the loud threshold is a percentage above thelowest magnitude. For example, if the sample with the lowest magnitudesince the current period of quietness began has a magnitude of 100 andthe loud threshold is based on a 20% increase in magnitude, thereverberation analyzer 212 sets the loud threshold to 120.

The example reverberation analyzer 212 determines that a sample is quietif the previous sample (n−1) is relatively loud and the magnitude of thecurrent sample (n) satisfies (e.g., is less than) a quiet threshold. Theexample reverberation analyzer 212 determines the quiet threshold basedon the amplitude of the loud sample when the audio signal 124 lasttransitioned from a relatively quiet sample to a relatively loud sample.Alternatively, in some examples, the example reverberation analyzer 212determines the quiet threshold based on the sample with the highestmagnitude since the most recent period of quiet ended. In some examples,the quiet threshold is a percentage less than the highest magnitude. Forexample, if the sample with the highest magnitude since the most recentperiod of quietness ended has a magnitude of 1000 and the quietthreshold is based on a 50% decrease in magnitude, the reverberationanalyzer 212 sets the quiet threshold to 500.

In some examples, to track transitions between a relatively quietsamples and a relatively loud samples, the reverberation analyzer 212maintains a loudness flag. In such examples, when a previous sample(n−1) is relatively quiet and the current sample (n) is relatively loud,the reverberation analyzer 212 sets the loudness flag to aloud-indicator value (e.g., a binary value representing the occurrenceof a relatively loud sample). Additionally, in such examples, when aprevious sample (n−1) is relatively loud and the current sample (n) isrelatively quiet, the reverberation analyzer 212 set the loudness flagto a quiet-indicator value (e.g., a binary value representing theoccurrence of a relatively quiet sample). In such examples, thereverberation analyzer 212 uses the loudness flag when determiningwhether the current sample (n) is loud or quiet instead of referring tothe previous sample (n−1). For example, if the loudness flag is set to aloud-indicator value, the reverberation analyzer 212 compares themagnitude of the current sample (n) to the quiet threshold.

In some examples, the AME 118 defines sample or time duration ranges forthe sample or time durations of the periods of loudness detected by thereverberation analyzer 212. A sample or time duration range encompassesa range of sample or time durations. For example, the AME 118 may definesample ranges in increments of 200 samples (e.g., a 1-200 sampleduration range, a 201-400 sample duration range, etc.). The sample ortime duration ranges are associated with a corresponding counter thatthe example reverberation analyzer 212 uses (e.g., increments) to trackquantities of periods of loudness in an audio block that fit within thesample or time duration ranges. In such examples, when determining theduration of a period of loudness, the reverberation analyzer 212increments the corresponding counter for the sample or time durationrange in which the period of loudness fits. For example, if thereverberation analyzer 212 determines that a period of loudness has asample duration of 406 samples, the reverberation analyzer 212increments a counter corresponding to a 401-600 sample duration range.In such a manner, the reverberation analyzer 212 does not need to retainthe specific durations of each period of loudness in the audio block. Insuch examples, the reverberation analyzer 212 calculates the shortloudness ratio (R_(SL)) by dividing the quantity of periods of loudnessin the sample or time duration ranges that are below a sample or timeduration threshold by the total quantity of periods of loudnessidentified using the counters corresponding to the duration ranges asshown in Equation 1 above. Table 1 below illustrates example sampleduration ranges and corresponding counter values calculated by thereverberation analyzer 212 to determine how many period of loudnessoccurred in an audio block.

TABLE 1 EXAMPLE AUDIO BLOCK ANALYZED BY THE REVERBERATION ANALYZERSample Duration Ranges of Number of Periods of Loudness Periods ofLoudness Detected (counter values) 2501-3000 1 2001-2500 3 1501-2000 71001-1500 8  501-1000 4  1-500 2In the examples illustrated in Table 1 above, if the sample durationthreshold is 1500 samples, the reverberation analyzer 212 calculates theshort loudness ratio (R_(SL)) for the audio block to be 56% ((14)/(25))based on Equation 1 above.

In the illustrated example, the spillover detector 214 obtains the shortloudness ratio (R_(SL)) for the audio block calculated by thereverberation analyzer 212 to determine if spillover occurred in theportion of the audio signal 124 corresponding to the audio block and themedia exposure data generated by the collector 204. To determine ifspillover occurred, the example spillover detector 214 compares theshort loudness ratio (R_(SL)) obtained from the reverberation analyzer212 with an example reverberation threshold. An example reverberationthreshold is set (e.g., by the AME 118) so that it will be satisfiedwhen the meter 200 receives an audio signal 124 from a mediapresentation device 108, 110 that is sufficiently near the meter 200such that the audio signal 124 is detected by the meter 200 in the sameroom in which it is emitted by the media presentation device 108, 110meaning that the detected audio signal is not spillover from anotherroom. In some examples, a reverberation threshold of 50% is sufficientto distinguish between spillover audio and non-spillover audio. In suchexamples, a 50% reverberation threshold means that 50% of the detectedperiods of loudness in an audio block were determined to be shortperiods of loudness. If the example spillover detector 214 determinesthat spillover did not occur, the example spillover detector 214instructs the example media evaluator 206 to mark the correspondingmedia exposure data as usable to award exposure credit to correspondingmedia. In some examples, if the spillover detector 214 determines thatspillover did occur, the example spillover detector 214 instructs themedia evaluator 206 to mark the corresponding media exposure data asinvalid (e.g., as corresponding to spillover) or unusable to awardexposure credit to corresponding media.

While an example manner of implementing the example meter 200 of FIG. 2is illustrated in FIG. 2, one or more of the elements, processes and/ordevices illustrated in FIG. 2 may be combined, divided, re-arranged,omitted, eliminated and/or implemented in any other way. Further, theexample receiver 202, the example collector 204, the example mediaevaluator 206, the example transmitter 208, the example spillovermanager 107 and/or, more generally, the example meter 200 of FIG. 2 maybe implemented by hardware, software, firmware and/or any combination ofhardware, software and/or firmware. Thus, for example, any of theexample receiver 202, the example collector 204, the example mediaevaluator 206, the example transmitter 208, the example spillovermanager 107 and/or, more generally, the example meter 200 could beimplemented by one or more analog or digital circuit(s), logic circuits,programmable processor(s), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example receiver202, the example collector 204, the example media evaluator 206, theexample transmitter 208, and/or the example spillover manager 107 is/arehereby expressly defined to include a tangible computer readable storagedevice or storage disk such as a memory, a digital versatile disk (DVD),a compact disk (CD), a Blu-ray disk, etc. storing the software and/orfirmware. Further still, the example meter 200 of FIG. 2 may include oneor more elements, processes and/or devices in addition to, or insteadof, those illustrated in FIG. 2, and/or may include more than one of anyor all of the illustrated elements, processes and devices.

While an example manner of implementing the example spillover manager107 of FIG. 1 is illustrated in FIG. 2, one or more of the elements,processes and/or devices illustrated in FIG. 2 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example audio sampler 210, the example reverberationanalyzer 212, the example spillover detector 214 and/or, more generally,the example spillover manager 107 of FIG. 1 may be implemented byhardware, software, firmware and/or any combination of hardware,software and/or firmware. Thus, for example, any of the example audiosampler 210, the example reverberation analyzer 212, the examplespillover detector 214 and/or, more generally, the example spillovermanager 107 could be implemented by one or more analog or digitalcircuit(s), logic circuits, programmable processor(s), applicationspecific integrated circuit(s) (ASIC(s)), programmable logic device(s)(PLD(s)) and/or field programmable logic device(s) (FPLD(s)). Whenreading any of the apparatus or system claims of this patent to cover apurely software and/or firmware implementation, at least one of theexample audio sampler 210, the example reverberation analyzer 212,and/or the example spillover detector 214 is/are hereby expresslydefined to include a tangible computer readable storage device orstorage disk such as a memory, a digital versatile disk (DVD), a compactdisk (CD), a Blu-ray disk, etc. storing the software and/or firmware.Further still, the example spillover manager 107 of FIG. 1 may includeone or more elements, processes and/or devices in addition to, orinstead of, those illustrated in FIG. 2, and/or may include more thanone of any or all of the illustrated elements, processes and devices.

FIGS. 3A, 3B, and 3C illustrate an example portion of an example audiosignal 124 analyzed by the example spillover manager 107 of FIGS. 1 and2. In the illustrated example of FIG. 3A, the audio signal 124 does nothave reverberation characteristics. The example audio sampler 210 (FIG.2) calculates an absolute magnitude audio signal 300 shown in FIG. 3B bycalculating the absolute values of the amplitudes of the audio signal124. The illustrated examples in FIG. 3C shows how the examplereverberation analyzer 212 (FIG. 2) detects long periods of loudness 302and short periods of loudness 304 in a portion 301 of the absolutemagnitude audio signal 300.

FIG. 3C illustrates a blown up view of the portion 301 of the absolutemagnitude audio signal 300 of FIG. 3B. In the illustrated example ofFIG. 3C, a plurality of samples (e.g., samples 306 a, 306 b, 306 c) forma portion of an audio block corresponding to the portion 301 of theabsolute magnitude audio signal 300. The illustrated example of FIG. 3Cshows example long periods of loudness 302 and example short periods ofloudness 304. The illustrated example also shows a loudness flag 308 totrack the state of the previous sample (n−1) used to determine whether acurrent sample (n) in the audio block is a relatively loud sample or arelatively quiet sample. The example loudness flag 308 is also used todetermine whether to (i) compare the amplitude of the current sample (n)to the quiet threshold 312, or (ii) compare the amplitude of the currentsample (n) to the amplitude of a previous sample (n−1).

The example audio sampler 210 samples the absolute magnitude audiosignal 300 at a sampling frequency to create the audio block of thesamples. In the illustrated example, to analyze the audio block, theexample reverberation analyzer 212 compares the current sample (n) toeither the quiet threshold or the amplitude of the pervious sample (n−1)based on the current state of the loudness flag 308. If the exampleloudness flag 308 is set to a quiet-indicator value (e.g., QUIET), theexample reverberation analyzer 212 compares the amplitude of the currentsample (n) to the amplitude of the previous sample (n−1). If the exampleloudness flag 308 is set to a loud-indicator value (e.g., LOUD), theexample reverberation analyzer 212 compares the current sample (n) to acurrent quiet threshold 312.

In the illustrated example of FIG. 3C, the loudness flag 308 was set toLOUD when the difference between the amplitude of the current sample (n)to the amplitude of the previous sample (n−1) satisfies (e.g., isgreater than) a loud threshold. In some examples, the value of the loudthreshold is a fixed value defined by the AME 118 (FIG. 1) or any othersuitable organization. Alternatively, the value of the loud threshold isrelative to the different between the amplitudes of the current sample(n) and the previous sample (n−1) when the loudness flag 308 was set toquiet.

In the illustrated example, the quiet threshold 312 is a value relativeto the amplitude of the sample when the loudness flag 308 was set toLOUD. For example, the quiet threshold 312 may be 80% of the amplitudeof the sample when the loudness flag 308 was set to LOUD. An example isillustrated in box 314. In the example, the first sample 306 a in thebox 314 does not satisfy the quiet threshold 312. Therefore, theloudness flag 308 remains set at LOUD. In the example, the second sample306 b in the box 314 satisfies the quiet threshold 312 and the loudnessflag 308 is set to QUIET. Therefore, the example reverberation analyzer212 identifies the second sample 306 b as a start of a period ofquietness. In the example, the third sample 306 c in the box 314 iscompared to the loud threshold. Because the difference between theamplitude of the third sample 306 c and the second sample 306 b is notgreater than the loud threshold, the loudness flag 308 remains set atQUIET.

In the illustrated example, when the loudness flag 308 transitions fromthe QUIET setting to the LOUD setting, the reverberation analyzer 212counts the number of samples for which the loudness flag 308 is set toLOUD. The example reverberation analyzer 212 compares that number ofsamples to a long threshold (TH_(L)). If the loudness flag 308transitions from the LOUD setting to the QUIET setting before the numberof samples satisfies the long threshold (TH_(L)), the examplereverberation analyzer 212 determines that the particular period ofloudness is a short period of loudness 304. Otherwise, if the number ofsamples satisfies the long threshold (TH_(L)) before the loudness flag308 transitions from the LOUD setting to the QUIET setting, the examplereverberation analyzer 212 determines that the particular period ofloudness is a long period of loudness 302.

In some examples, the example reverberation analyzer 212 determineswhether, after the loudness flag 308 transitions from the LOUD settingto the QUIET setting, the loudness flag 308 transitions from the QUIETsetting to the LOUD setting before a number of samples satisfies a quietlength threshold (TH_(Q)). If the loudness flag 308 transitions from theQUIET setting to the LOUD setting before the number of samples satisfiesthe quiet length threshold (TH_(Q)), example reverberation analyzer 212determines that the particular period of loudness did not end andcontinues to count the number of samples for which the loudness flag 308is set to LOUD. Otherwise, if the loudness flag 308 does not transitionfrom the QUIET setting to the LOUD setting before the number of samplessatisfies the quiet threshold (TH_(Q)), example reverberation analyzer212 determines that the particular period of loudness did end.

FIGS. 4A, 4B, and 4C illustrate another example portion of an exampleaudio signal 124 analyzed by the example spillover manager 107 of FIGS.1 and 2. In the illustrated example of FIG. 4A, the audio signal 124 hasreverberation characteristics. The example audio sampler 210 (FIG. 2)calculates an absolute magnitude audio signal 400 by calculating theabsolute values of the amplitudes of the audio signal 124 shown in FIG.4B. The examples illustrated in FIG. 4C shows how the examplereverberation analyzer 212 (FIG. 2) detects long periods of loudness 302and short periods of loudness 304 in a portion 401 of the absolutemagnitude audio signal 400 having reverberation characteristics.

FIG. 4C illustrates a blown up view of the portion 401 of the absolutemagnitude audio signal 400 of FIG. 4B. In the illustrated example ofFIG. 4C, the plurality of samples form a portion of an audio blockcorresponding to the portion 401 of the absolute magnitude audio signal400. The illustrated example of FIG. 4C shows example long periods ofloudness 302. In the illustrated examples, reverberation characteristicshave eliminated the short periods of loudness 304 (FIG. 3C) in the blownup view of the portion 401. The illustrated example also shows theloudness flag 308 to track the state of the previous sample (n−1) usedto determine whether a current sample (n) in the audio block is arelatively loud sample or a relatively quiet sample.

The example audio sampler 210 samples the absolute magnitude audiosignal 400 at a sampling frequency to create the audio block. In theillustrated example, to analyze the audio block, the examplereverberation analyzer 212 either i) compares the amplitude of thecurrent sample (n) to the quiet threshold 312, or (ii) compares theamplitude of the current sample (n) to the amplitude of a previoussample (n−1) based on the current state of a loudness flag 308. If theexample loudness flag 308 is set to a quiet-indicator value (e.g.,QUIET), the example reverberation analyzer 212 compares the differencebetween the amplitude of the current sample (n) and the amplitude of theprevious sample (n−1) to the loud threshold. If the example loudnessflag 308 is set to a loud-indicator value (e.g., LOUD), the examplereverberation analyzer 212 compares the current sample (n) to a currentquiet threshold 312. In the illustrated example of FIG. 4C, the loudthreshold is a fixed value (e.g., 500, 1000, etc.). In the illustratedexample, the quiet threshold 312 is a value relative to the amplitude ofthe audio signal 124 when the loudness flag 308 was set to LOUD. In theexample illustrated in FIG. 4C, because the audio signal 124, and thusthe absolute magnitude audio signal 400, has reverberationcharacteristics, the total number of periods of loudness tend to befewer and/or longer (e.g., than the absolute value audio signal 300 ofFIGS. 3B and 3C) As a result, as illustrated in FIG. 4C, the relativequantity of the short periods of loudness 304 also tend to be fewer.

A flowchart representative of example machine readable instructions forimplementing the example meter 200 of FIG. 2 is shown in FIG. 5.Flowcharts representative of example machine readable instructions forimplementing the example spillover manager 107 of FIGS. 1 and 2 areshown in FIGS. 6, and 7A, 7B. In this example, the machine readableinstructions comprise a program for execution by a processor such as theprocessor 812 shown in the example processor platform 800 discussedbelow in connection with FIG. 8. The program may be embodied in softwarestored on a tangible computer readable storage medium such as a CD-ROM,a floppy disk, a hard drive, a digital versatile disk (DVD), a Blu-raydisk, or a memory associated with the processor 812, but the entireprogram and/or parts thereof could alternatively be executed by a deviceother than the processor 812 and/or embodied in firmware or dedicatedhardware. Further, although the example program(s) is/are described withreference to the flowcharts illustrated in FIGS. 5, 6, 7A, and 7B manyother methods of implementing the example meter 200 and/or the examplespillover manager 107 may alternatively be used. For example, the orderof execution of the blocks may be changed, and/or some of the blocksdescribed may be changed, eliminated, or combined.

As mentioned above, the example processes of FIGS. 5, 6, 7A, and 7B maybe implemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a tangible computer readable storagemedium such as a hard disk drive, a flash memory, a read-only memory(ROM), a compact disk (CD), a digital versatile disk (DVD), a cache, arandom-access memory (RAM) and/or any other storage device or storagedisk in which information is stored for any duration (e.g., for extendedtime periods, permanently, for brief instances, for temporarilybuffering, and/or for caching of the information). As used herein, theterm tangible computer readable storage medium is expressly defined toinclude any type of computer readable storage device and/or storage diskand to exclude propagating signals and to exclude transmission media. Asused herein, “tangible computer readable storage medium” and “tangiblemachine readable storage medium” are used interchangeably. Additionallyor alternatively, the example processes of FIGS. 5, 6, 7A and 7B may beimplemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a non-transitory computer and/ormachine readable medium such as a hard disk drive, a flash memory, aread-only memory, a compact disk, a digital versatile disk, a cache, arandom-access memory and/or any other storage device or storage disk inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, for brief instances, for temporarily buffering,and/or for caching of the information). As used herein, the termnon-transitory computer readable medium is expressly defined to includeany type of computer readable storage device and/or storage disk and toexclude propagating signals and to exclude transmission media. As usedherein, when the phrase “at least” is used as the transition term in apreamble of a claim, it is open-ended in the same manner as the term“comprising” is open ended.

FIG. 5 is a flow diagram representative of example machine readableinstructions 500 that may be executed to implement the example meter 200of FIG. 2 to create media exposure data usable to award exposure creditto the corresponding media. The example meter 200 may be a stationarymeter (e.g., the meters 102, 104 of FIG. 1) or a portable meter (e.g.,the meter 106 of FIG. 1). The meter 200 uses the spillover manager 107(FIGS. 1 and 2) to reduce media monitoring inaccuracies by detectingspillover and indicating that media exposure data is usable to awardexposure credit to the corresponding media when spillover does notoccur. Initially, at block 502, the example collector 204 determineswhether media exposure data can be created for a time-based interval(e.g., a one-second interval, a five-second interval, etc.) of an audiosignal 124. The example collector 204 determines that media exposuredata can be created if a code can be extracted and/or signature can begenerated from the time-based interval of audio signal 124 beinganalyzed. If exposure data can be created for the time-based interval ofthe received audio signal 124, program control advances to block 504.Otherwise, if media exposure data cannot be created for the time-basedinterval of the audio signal 124, program control advances to block 516.

At block 504, the example spillover manager 107 analyzes the time-basedinterval of the audio signal 124 analyzed by the collector 204 to detectwhether spillover has occurred. Example methods to detect if spilloveroccurred are described below in connection with FIGS. 6, and 7A, 7B, 7C.At block 506, the spillover manager 107 determines whether was spilloverdetected in the time-based interval of the audio signal analyzed atblock 504. If the example spillover manager 107 determines thatspillover occurred, program control advances to block 508. Otherwise, ifthe example spillover manager 107 determines that spillover did notoccur, program control advances to block 512. At block 508, the examplemedia evaluator 206 does not mark the exposure data as usable to awardexposure credit to the correspond media. At block 510, the example mediaevaluator 206 discards the media exposure data. Program control thenadvances to block 516.

At block 512, the media evaluator 206 marks the media exposure data asusable to award exposure credit to the corresponding media. At block514, the example transmitter 208 transmits the media exposure datamarked as usable to award exposure credit to the corresponding media tothe AME 118. At block 516, the meter 200 determines whether to continueto monitor for media. For example, the meter 200 determines whether itcan still detect the audio signal 124. If the meter 200 determines thatit is to continue to monitor for media, program control returns to block502; otherwise, example program 500 ends.

FIG. 6 is a flow diagram representative of example machine readableinstructions 504 that may be executed to implement the example spillovermanager 107 of FIGS. 1 and 2 to detect spillover in an audio signal 124.Initially, at block 602, the example audio sampler 210 samples (e.g.,digitizes the audio signal 124 using a sampling frequency) a time-basedinterval of the audio signal 124 to generate an audio block of samplesrepresentative of the time-based interval of the audio signal 124. Atblock 604, the example reverberation analyzer 212 analyzes the audioblock generated at block 602 to identify the periods of loudness in theaudio block. An example method to identify the periods of loudness inthe audio block is described below in connection with FIGS. 7A, 7B, and7C. At block 606, the example reverberation analyzer 212 determines aquantity of the periods of loudness identified at block 604 that satisfythe duration threshold. At block 608, the example reverberation analyzer212 calculates a short loudness ratio (R_(SL)) by dividing the quantityof the periods of loudness that satisfy a duration threshold determinedat block 606 by a total number periods of loudness in the audio blockidentified at block 604.

At block 610, the example spillover detector 214 determines whether theshort loudness ratio (R_(SL)) calculated at block 608 satisfies (e.g.,is greater than) a loud threshold. If the example spillover detector 214determines that the short loudness ratio (R_(SL)) does not satisfy(e.g., is less than) the loud threshold, program control advances toblock 612. Otherwise, if the example spillover detector 214 determinesthat the short loudness ratio (R_(SL)) does satisfy (e.g., is greaterthan) the loud threshold, program control advances to block 614. Atblock 612, the spillover detector 214 indicates (e.g., sends aninstruction to the media evaluator 206 of FIG. 2) that spilloveroccurred in the portion of the audio signal 124 corresponding to theaudio block generated by the audio sampler 210 at block 602. The exampleprogram 600 then ends. At block 612, the spillover detector 214indicates (e.g., sends an instruction to the media evaluator 206) thatspillover did not occur in the portion of the audio signal 124corresponding to the audio block generated by the audio sampler 210 atblock 602. The example program 600 then ends.

FIGS. 7A and 7B are flow diagrams representative of example machinereadable instructions 604 that may be executed to implement the examplereverberation analyzer 212 of FIG. 2 to detect periods of loudness in anaudio signal (e.g., the audio signal 124 of FIGS. 1 and 2). Initially,at block 702 (FIG. 7A), the example reverberation analyzer 212initializes the loudness flag (e.g., the loudness flag 308 of FIGS. 3Cand 4C), the sample duration counter, and the quiet duration counter. Insome examples, the loudness flag 308 is set to the quiet-indicatorvalue, the sample duration counter is set to zero, and/or the quietduration counter is set to zero. At block 704, the example reverberationanalyzer 212 obtains a new current sample (n) (e.g. the next sample tobe analyzed) from the audio block. At block 706, the examplereverberation analyzer 212 determines whether the loudness flag 308 isset to the quiet-indicator value. If the loudness flag 308 is set to thequiet-indicator value, program control advances to block 708. Otherwise,if the loudness flag 308 is not set to the quiet-indicator value,program control advances to block 714.

At block 708, the example reverberation analyzer 212 determines whetherthe difference between the amplitude of the current sample (n) and theprevious sample (n−1) satisfies (e.g., is greater than) the loudthreshold. If the difference between the amplitude of the current sample(n) and the previous sample (n−1) satisfies the loud threshold, programcontrol advances to block 710. Otherwise, if the difference between theamplitude of the current sample (n) and the previous sample (n−1) doesnot satisfy (e.g., is less than or equal to) the loud threshold, programcontrol advances to block 714. At block 710, the example reverberationanalyzer 212 sets the loudness flag to the loud-indicator value. Atblock 712, the example reverberation analyzer 212 determines the quietthreshold (e.g., the quiet threshold 312 of FIGS. 3C and 4C). In someexamples, the quiet threshold is a percentage of the amplitude of thecurrent sample (n). For example, the quiet threshold may be 80% of theamplitude of the current sample (n). At block 714, the examplereverberation analyzer 212 sets the previous sample (n−1) to be thecurrent sample (n). Program control then advances to block 716 (FIG.7B).

At block 716, the example reverberation analyzer 212 determines whetherthe loudness flag 308 is set to the quiet-indicator value. If theloudness flag 308 is set to the quiet-indicator value, program controladvances to block 734 (FIG. 7A). Otherwise, if the loudness flag 308 isset to the loud-indicator value, program control advances to block 718.At block 718, the example reverberation analyzer 212 increments thesample duration counter. At block 720, the example reverberationanalyzer 212 determines whether the amplitude of the current sample (n)satisfies (e.g. is less than) the quiet threshold 312. If the amplitudeof the current sample (n) satisfies the quiet threshold 312, programcontrol advances to block 722. Otherwise, if the amplitude of thecurrent sample (n) does not satisfy the quiet threshold 312, programcontrol advances to block 724. At block 722, the example reverberationanalyzer 212 increments the quiet length. At block 724, the examplereverberation analyzer 212 sets the quiet length to zero.

At block 726, the example reverberation analyzer 212 determines whetherthe quiet length satisfies a quiet length threshold (TH_(Q)). If thequiet length satisfies the quiet length threshold (TH_(Q)), programcontrol advances to block 728. Otherwise, if the quiet length does notsatisfy the quiet length threshold (TH_(Q)), program control advances toblock 734 (FIG. 7A). At block 728, the example reverberation analyzer212 increments a sample duration range counter corresponding to thesample duration range that the value of the sample duration counterfalls within. For example, if the value of the duration range counter is1842, the example reverberation analyzer 212 increments the sampleduration range counter corresponding to 1800-2000 samples. At block 730,the example reverberation analyzer 212 set the loudness flag 308 to thequiet-indicator value. At block 732, the reverberation analyzer 212resets the quiet threshold (e.g., to zero), the quiet length (e.g., tozero), and the sample duration counter (e.g., to zero). Program controladvances to block 734 (FIG. 7A).

At block 734 (FIG. 7A), the example reverberation analyzer 212determines whether there is another sample in the audio block. If thereis another sample, program control returns to block 704. Otherwise, ifthere is not another sample in the audio block, example program 604ends.

FIG. 8 is a block diagram of an example processor platform 800structured to execute the instructions of FIGS. 5, 6, and/or 7A, 7B toimplement the example meter 200 of FIG. 2 and/or the example spillovermanager of FIGS. 1 and 2. The processor platform 800 can be, forexample, a server, a personal computer, a mobile device (e.g., a cellphone, a smart phone, a tablet such as an iPad™), a personal digitalassistant (PDA), a set top box, or any other type of computing device.

The processor platform 800 of the illustrated example includes aprocessor 812. The processor 812 of the illustrated example is hardware.For example, the processor 812 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors or controllers fromany desired family or manufacturer. In the illustrated example, theprocessor 812 includes an example audio sampler 210, an examplereverberation analyzer 212, and an example spillover detector 214.

The processor 812 of the illustrated example includes a local memory 813(e.g., a cache). The processor 812 of the illustrated example is incommunication with a main memory including a volatile memory 814 and anon-volatile memory 816 via a bus 818. The volatile memory 814 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM)and/or any other type of random access memory device. The non-volatilememory 816 may be implemented by flash memory and/or any other desiredtype of memory device. Access to the main memory 814, 816 is controlledby a memory controller.

The processor platform 800 of the illustrated example also includes aninterface circuit 820. The interface circuit 820 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), and/or a PCI express interface.

In the illustrated example, one or more input devices 822 are connectedto the interface circuit 820. The input device(s) 822 permit(s) a userto enter data and commands into the processor 812. The input device(s)can be implemented by, for example, an audio sensor, a microphone, acamera (still or video), a keyboard, a button, a mouse, a touchscreen, atrack-pad, a trackball, isopoint and/or a voice recognition system.

One or more output devices 824 are also connected to the interfacecircuit 820 of the illustrated example. The output devices 824 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay, a cathode ray tube display (CRT), a touchscreen, a tactileoutput device, a printer and/or speakers). The interface circuit 820 ofthe illustrated example, thus, typically includes a graphics drivercard, a graphics driver chip or a graphics driver processor.

The interface circuit 820 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem and/or network interface card to facilitate exchange of data withexternal machines (e.g., computing devices of any kind) via a network826 (e.g., an Ethernet connection, a digital subscriber line (DSL), atelephone line, coaxial cable, a cellular telephone system, etc.).

The processor platform 800 of the illustrated example also includes oneor more mass storage devices 828 for storing software and/or data.Examples of such mass storage devices 828 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, RAIDsystems, and digital versatile disk (DVD) drives.

Coded instructions 832 of FIGS. 5, 6, and/or 7A, 7B may be stored in themass storage device 828, in the volatile memory 814, in the non-volatilememory 816, and/or on a removable tangible computer readable storagemedium such as a CD or DVD.

From the foregoing, it will appreciate that examples have been disclosedwhich allow a meter 200 (FIG. 2) to detect spillover in an audio signalof a media presentation while conserving processor resources. As aresult, a spillover manager 107 (FIGS. 1 and 2) may located on the meter200. Thus, the meter 200 makes the determination of whether spilloveroccurred instead of requiring another device in the panelist home (e.g.,the home processing system 114 of FIG. 1). Because the spillover manager107 is located on the meter 200, the audio signal does not need to besaved and sent to the home processing system 114. Thus, the examplesthat have been disclosed that conserve bandwidth.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

1. A method to credit media in a media measuring system, comprising:determining, by executing an instruction with a processor, periods ofloudness in an audio signal of the media presented by a mediapresentation device; identifying, by executing an instruction with theprocessor, a quantity of the periods of loudness that satisfy a durationthreshold; calculating, by executing an instruction with the processor,a ratio of the quantity of the periods of loudness that satisfy theduration threshold and a total number of periods of loudness in themedia; and marking, by executing an instruction with the processor, themedia as un-usable to credit a media exposure when the ratio does notsatisfy a loud threshold, the marking of the media to improve theaccuracy of the media exposure credit by excluding media havingindications of spillover.
 2. The method as defined in claim 1, whereinthe determining of the periods of loudness in the audio signal of themedia includes identifying a first transition and a second transition inthe audio signal of the media.
 3. The method as defined in claim 2,wherein the first transition occurs when a loudness flag transitionsfrom a loud-indicator value to a quiet-indicator value.
 4. The method asdefined in claim 3, wherein the loudness flag is set to thequiet-indicator value when a sample of the audio signal satisfies aquiet threshold, the quiet threshold being based on a most recent peakvalue of the audio signal.
 5. The method as defined in claim 2, whereinthe second transition occurs when a loudness flag transitions from aquiet-indicator value to a loud-indicator value.
 6. The method asdefined in claim 5, wherein the loudness flag is set to theloud-indicator value when a sample of the audio signal satisfies theloud threshold, the loud threshold being based on a most recent dipvalue of the audio signal.
 7. The method as defined in claim 2, whereina duration of one of the periods of loudness is a number of samples ofthe audio signal between the first transition and the second transitionof the one of the periods of loudness.
 8. An apparatus comprising: areverberation analyzer to: determine periods of loudness in an audiosignal of media presented by a media presentation device, identify aquantity of the periods of loudness that satisfy a duration threshold,and calculate a ratio of the quantity of the periods of loudness thatsatisfy the duration threshold and a total number of periods of loudnessin the media; and a spillover detector to mark the media as un-usable tocredit a media exposure when the ratio does not satisfy a loudthreshold, the marking of the media to improve the accuracy of the mediaexposure credit by excluding media having indications of spillover. 9.The apparatus as defined in claim 8, wherein to determine the periods ofloudness in the audio signal of the media, the reverberation analyzer isto detect a first transition and a second transition in the audio signalof the media.
 10. The apparatus as defined in claim 9, wherein thereverberation analyzer is to detect the first transition occurs when aloudness flag transitions from a loud-indicator value to aquiet-indicator value.
 11. The apparatus as defined in claim 10, whereinthe loudness flag is set to the quiet-indicator value when a sample ofthe audio signal satisfies a quiet threshold, the quiet threshold beingbased on a most recent peak value of the audio signal.
 12. The apparatusas defined in claim 9, wherein the reverberation analyzer is to detectthe second transition when a loudness flag transitions from aquiet-indicator value to a loud-indicator value.
 13. The apparatus asdefined in claim 12, wherein the loudness flag is set to theloud-indicator value when a sample of the audio signal satisfies theloud threshold, the loud threshold being based on a most recent dipvalue of the audio signal.
 14. The apparatus as defined in claim 9,wherein the reverberation analyzer is to calculate a duration of one ofthe periods of loudness by determining a number of samples of the audiosignal between the first transition and the second transition of the oneof periods of loudness.
 15. A tangible computer readable storage mediumcomprising instructions that, when executed, cause a machine to atleast: determine periods of loudness in an audio signal of mediapresented by a media presentation device; identify a quantity of theperiods of loudness that satisfy a duration threshold; calculate a ratioof the quantity of the periods of loudness that satisfy the durationthreshold and a total number of periods of loudness in the media; andmark the media as un-usable to credit a media exposure when the ratiodoes not satisfy a loud threshold, the marking of the media to improvethe accuracy of the media exposure credit by excluding media havingindications of spillover.
 16. The computer readable storage medium asdefined in claim 15, wherein the instructions are further to cause themachine to determine the periods of loudness in the audio signal of themedia by identifying a first transition and a second transition in anaudio signal of the media.
 17. The computer readable storage medium asdefined in claim 16, when executed, wherein the instructions are furtherto cause the machine to identify the first transition when a loudnessflag transitions from a loud-indicator value to a quiet-indicator value.18. The computer readable storage medium as defined in claim 17, whereinthe loudness flag is set to the quiet value when a sample of the audiosignal satisfies a quiet threshold, the quiet threshold being based on amost recent peak value of the audio signal.
 19. The computer readablestorage medium as defined in claim 16, wherein the instructions arefurther to cause the machine to identify the second transition when aloudness flag transitions from a quiet-indicator value to aloud-indicator value.
 20. The computer readable storage medium asdefined in claim 19, wherein the loudness flag is set to the loud valuewhen a sample of the audio signal satisfies the loud threshold, the loudthreshold being based on a most recent dip value of the audio signal.